Summary
✨ AI‑Generated
A Generative AI Engineer is sought for a hybrid contract role focused on building practical AI agents and automation tools that improve business operations. The work involves analyzing real-world processes, identifying high-impact inefficiencies, designing lean AI solutions, deploying them quickly, and measuring results against defined baselines while retaining human oversight.
Highlights
Contract role combining generative AI engineering with practical business process improvement. The work emphasizes measurable operational outcomes, rapid deployment, lean solutions, AI agents, and human approval for important decisions across multiple industries.
Description
Company Description Cintelis AI is an evidence-led business improvement firm based in Brisbane, Australia, focused on delivering measurable operational gains rather than reports and slide decks.
The team analyzes how processes actually run—where time is spent, where work waits, and what tasks truly cost—then designs AI agents and tools to close the most impactful gaps.
Every deployment is measured against a baseline, with results transparently reported, and solutions are built to run inside the client’s business with human approval for key decisions.
Cintelis AI emphasizes lean builds, fast deployment, and practical automation that clients typically see the benefits of within weeks.
With more than fifteen years of hands-on delivery across aged care, financial services, government, and professional services, the firm brings deep domain insight to uncover and remove hidden sources of inefficiency.
Role Description This is a contract Generative AI Engineer role in a hybrid working arrangement, based in Brisbane, QLD, with the option to work from home part of the time.
The Generative AI Engineer will design, develop, and deploy AI agents and generative pipelines that automate high-impact business processes while keeping humans in control of critical decisions.
Day-to-day responsibilities include analyzing client workflows, building and integrating AI models and tools, implementing data flows and orchestration logic, and iterating solutions based on measured outcomes.
The role involves close collaboration with business stakeholders to translate process insights into technical designs, as well as documenting systems, testing performance against baseline metrics, and refining models for accuracy, reliability, and safety.
The engineer will also help ensure that solutions are transparent, maintainable, and cost-effective, avoiding unnecessary complexity and vendor lock-in.
Qualifications
Strong skills in designing and implementing generative AI solutions, including experience with large language models (LLMs), prompt engineering, and multi-agent workflows.Proficiency in programming for AI systems (e.g., Python), including building APIs, data pipelines, and tool integrations that connect models to real-world business processes.Experience with cloud platforms and AI tooling (such as major cloud providers, ML frameworks, or orchestration libraries) to deploy, monitor, and scale production AI services.Capability in process analysis and measurement, including mapping workflows, quantifying time and cost, and using data to validate improvements and guide iteration.Solid understanding of software engineering practices, including version control, testing, documentation, and secure handling of data in enterprise-like environments.Effective communication and collaboration skills, with the ability to work directly with non-technical stakeholders to clarify requirements and explain AI systems and results.Prior experience delivering automation or AI solutions in sectors such as financial services, government, aged care, or professional services is highly
